Source-level EEG and graph theory reveal widespread functional network alterations in focal epilepsy

Objective: The hypersynchronous neuronal activity associated with epilepsy causes widespread functional network disruptions extending beyond the epileptogenic zone. This altered network topology is considered a mediator for non-seizure symptoms, such as cognitive impairment. The aim of this study was to investigate functional network alterations in focal epilepsy patients with good seizure control and high quality of life. Methods: We compared twenty-two focal epilepsy patients and sixteen healthy controls on graph metrics derived from functional connectivity of source-level resting-state EEG. Graph metrics were calculated over a range of network densities in five frequency bands. Results: We observed a significantly increased small world index in patients relative to controls. On the local level, two left-hemisphere regions displayed a shift towards greater alpha band "hubness". The findings were not mediated by age, sex or education, nor by age of epilepsy onset, duration or focus lateralisation. Conclusions: Widespread functional network alterations are evident in focal epilepsy, even in a cohort characterised by successful anti-seizure medication therapy and high quality of life. These findings might support the position that functional network analysis could hold clinical relevance for epilepsy. Significance: Focal epilepsy is accompanied by global and local functional network aberrancies which might be implied in the sustenance of non-seizure symptoms. (c) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Effect of obesity on constant workrate exercise in hyperinflated men with COPD

<p>Abstract</p> <p>Background</p> <p>Chronic obstructive pulmonary disease (COPD) and a high body mass index (BMI) can both affect pulmonary volumes as well as exercise tolerance, but their combined effect on these outcomes is not well known. The aim of this study was to investigate the effects of increased BMI during constant workrate cycle ergometry in patients with COPD.</p> <p>Methods</p> <p>Men with COPD and hyperinflation were divided according to World Health Organization BMI classification: 84 normal BMI (NBMI), 130 overweight (OW) and 64 obese (OB). Patients underwent spirometric and lung volumes assessment and an incremental cycling exercise test. This was followed by a constant workrate exercise test (CET) at 75% of peak capacity. Inspiratory capacity and Borg dyspnea scores were measured at baseline, during and at the end of CET.</p> <p>Results and discussion</p> <p>FEV₁% predicted was not different across BMI classes. Total lung capacity and functional residual capacity were significantly lower in OB and OW compared to NBMI patients. Peak VO₂in L·min^-1was significantly higher in OB and OW patients than in NBMI patients. CET time was not different across BMI classes (p = 0.11). Changes in lung volumes and dyspnea during CET were not different between BMI categories.</p> <p>Conclusions</p> <p>OB and OW patients with COPD had a higher peak VO₂than their lean counterparts. Endurance time, dyspnea and changes in lung volumes during CET were similar between BMI categories.</p

Analysis strategies for high-resolution UHF-fMRI data

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential